{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# 如何学习中餐菜谱"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "大概过年的时候围观了一篇这样的文章：\n",
    "[food2vec - Augmented cooking with machine intelligence](https://jaan.io/food2vec-augmented-cooking-machine-intelligence/)\n",
    "\n",
    "讲了一个把食物向量化的一个应用，还挺好玩的。\n",
    "\n",
    "转念一想，我大天朝物产丰富，在吃的方面绝对要比世界人民领先好几个档次，当然也是可以搞一搞这个的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### 数据预处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "首先就是数据了，俗话说：“巧妇难为无米之炊。”没有数据，我这个“小厨师”也干不了活。\n",
    "\n",
    "我们先找到一个菜谱大全的文本文件，命名为“recipe.txt”。\n",
    "\n",
    "涉及中文字符处理，先把所有的字符串转成`Unicode`："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from __future__ import unicode_literals"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "中文文件的编码向来是个大坑，这里我把文件转成了比较通用的UTF-8格式编码。可以用`codecs`模块指定编码格式来读取文件："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "import codecs\n",
    "with codecs.open(\"data/recipe.txt\", encoding=\"utf8\") as f:\n",
    "    raw_data = f.read().strip().split(\"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "我对数据做了一些简单的预处理，现在我们的数据长这个样子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "﻿【菜名】板栗烧鸡【所属菜系】东北菜【特点】鸡肉酥烂，板栗香甜，时令佳肴，美味可口【原料】活雌鸡或阉鸡1只，约重1500～2000克，菜油（或化猪油）100克，豆瓣25克，老姜50克，大葱10克，白糖或冰糖25克，花椒、料酒、酱油、精盐、味精、八角等适量。【制作过程】将鸡宰杀、拔毛、剖腹去内脏洗净，把鸡头、翅膀和脚至胫部切下，然后将鸡对剖开，将鸡肉斩成长3厘米、宽2厘米的长方块，把鸡头、翅膀和脚也斩成3厘米的段。锅置旺火上，下100克菜油烧热，然后将鸡块入热油锅中爆炒，待鸡肉变硬时，加入料酒及姜块、豆瓣、花椒，炒至水分渐干溢出香味时，即掺入适量水，放入少量盐、酱油和白糖、八角等。加盖焖烧至六七成熟时，再加入板栗同烧15分钟左右即可。起锅时加入葱段及味精，有少量汤汁为宜。\r\n",
      "【菜名】鸳鸯戏飞龙【所属菜系】东北菜【特点】【原料】飞龙肉200克，鸡脯肉50克，口蘑、蛋清、火腿、菜心适量。【制作过程】1.飞龙肉切薄片，用蛋清糊上浆，下开水锅汆透捞出；2.用150克蛋清搅成蛋泡糊，鸡脯肉制成茸，加在蛋泡糊中拌匀，倒在模子中成鸳鸯形，用红、绿辣椒饰嘴、眼及翅膀，上笼蒸熟取出；3.飞龙片、火腿片、鲜蘑、油菜心下鸡清汤中烧开捞入碗中，余汤烧开撇净浮沫，调好味后倒入汤碗，再放入蒸好的鸳鸯即成。\r\n",
      "【菜名】木樨肉【所属菜系】东北菜【特点】【原料】猪瘦肉150克，鸡蛋150克，干木耳5克，黄瓜克，盐5克，酱油3克，料酒5克，油80克，香油料克。【制作过程】将猪瘦肉切成长5、宽0.3、厚0.3厘米的丝。鸡蛋磕入碗中，用筷子打匀；干木耳加开水泡5分钟，去掉根部，撕成块。黄瓜斜刀切成长2厘米的段，放平后直刀切成片，片形状即为菱形。葱、姜切成丝；③炒锅上火，加油，烧热后加入鸡蛋炒散，使其成为不规则小块，盛装在盘中，即为所说的木须；④炒锅上火，加油烧热，将肉丝放入煸炒，肉色变白后，加入葱、姜丝同炒，至八成熟时，加入料酒、酱油、盐，炒匀后加入木耳、黄瓜和鸡蛋块同炒，成熟后淋入香油即可。\r\n",
      "【菜名】白肉血肠【所属菜系】东北菜【特点】【原料】鲜带皮猪五花肉一方，猪大肠500克，鲜猪血1000克【制作过程】（1）带皮猪五花肉皮朝下用明火把皮烧焦，在温水中泡半个小时取，刮净焦皮，下开水锅中煮开后，用小火煮透，趁热抽去肋骨，晾凉后切薄片装盘。（2）猪肥肠治净，皮朝内翻出，一头扎紧。（3）鲜猪血澄清，上部血清加1/4清水、盐、味精及用砂仁、桂皮、企边桂、紫蔻、丁香合制的调料面搅匀，倒入猪肠中，扎紧封口，下开水锅用小火煮至浮出，捞出晾凉切片，下水锅中焯透捞如汤碗只，加葱花、姜丝、味精等调料及肉汤，随白肉一同上桌即可。\r\n",
      "【菜名】鸳鸯戏飞龙【所属菜系】东北菜【特点】【原料】飞龙肉200克，鸡脯肉50克，口蘑、蛋清、火腿、菜心适量【制作过程】（1）飞龙肉切薄片，用蛋清糊上浆，下开水锅汆透捞出；（2）用150克蛋清搅成蛋泡糊，鸡脯肉制成茸，加在蛋泡糊中拌匀，倒在模子中成鸳鸯形，用红、绿辣椒饰嘴、眼及翅膀，上笼蒸熟取出；（3）飞龙片、火腿片、鲜蘑、油菜心下鸡清汤中烧开捞入碗中，余汤烧开撇净浮沫，调好味后倒入汤碗，再放入蒸好的鸳鸯即成。\r\n"
     ]
    }
   ],
   "source": [
    "for line in raw_data[:5]:\n",
    "    print line"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "每一行是一个数据，包括菜名、菜系、特点、原料、做法等细节。\n",
    "\n",
    "先看一眼有多少个菜谱："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4577"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(raw_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "先来定义一个函数处理每一条数据，每行数据规律性还挺明显的，这里我用正则表达式提取相关信息："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def process_single_data(line):\n",
    "    pattern = r\"【菜名】([^【]*)【所属菜系】([^【]*)【特点】([^【]*).*【原料】([^【]*).*【制作过程】([^【]*).*\"\n",
    "    match = re.search(pattern, line)\n",
    "    if match:\n",
    "        return {\"菜名\": match.group(1), \n",
    "                \"菜系\": match.group(2), \n",
    "                \"特点\": match.group(3), \n",
    "                \"原料\": match.group(4),\n",
    "                \"过程\": match.group(5)}\n",
    "    print \"处理下列数据出现错误：\", line"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "随便处理一行试试："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "特点 \n",
      "菜名 香露全鸡\n",
      "过程 1.将鸡治净，从背部剖开，再横切3刀，鸡腹向上放入炖钵，铺上火腿片、香菇，加入调料、鸡汤。2.钵内放入盛有高粱酒、丁香的小杯，加盖封严，蒸2小时后取出钵内小杯即成。\r\n",
      "菜系 闽菜\n",
      "原料 肥嫩母鸡1只，水发香菇2朵，火腿肉2片，高粱酒50克，鸡汤750克，丁香子5粒\n"
     ]
    }
   ],
   "source": [
    "sample = process_single_data(raw_data[1105])\n",
    "\n",
    "for k in sample:\n",
    "    print k, sample[k]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "对所有的数据进行处理："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data = map(process_single_data, raw_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "在建模之前，我们先看看数据的分布。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### 中文画图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "涉及画图，我们先导入必要的画图工具："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "而且需要解决不显示中文的问题："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAEICAYAAABcVE8dAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n4EtSEwZfkpow+JLUhMGXpCYMviQ18b9wdXjoEfdPqAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8b4b3bce50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"中文\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "显示不出中文是因为它找不到合适的字体去显示。\n",
    "\n",
    "为此，我们可以使用`FontProperties`指定字体的路径来生成一个字体对象，然后画图的时候指定字体。\n",
    "\n",
    "我个人比较喜欢简单粗暴，所以都是直接找到字体文件，放在当前文件夹直接用，比如宋体："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from matplotlib.font_manager import FontProperties\n",
    "font_song = FontProperties(fname=\"SIMSUN.TTC\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4PmN3Va36M0TOY13+jXyWwaN7kmxmcIrn2CSHnJAue/Et4JUASV7MIPinJjrl+WEOeN3w\n1TrXAo9X1bdX+qaxntIpP5bhxzruxfuAZwKfHj5v/a2q2j21ocek4140oeNeHAJ+O8lR4EfA26pq\n3f0V3HEv3gr8Q5K/YPAE7s3r8QFikk8y+CW/efh8xTuBZwBU1QcZPH+xC1gAngBe3+l21+FeSZKW\n4TttJakRBl+SGmHwJakRBl+SGmHwJakRBl+SGmHwJakRBl+SGvH/eDfaqvFphfgAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8b490cbed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"中文\", fontproperties=font_song)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### 菜系统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data_tps = [s[\"菜系\"] for s in data]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "先看看有哪些菜系和数目，计数这种任务交给Counter就好了："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "沪菜 87\n",
      "浙江菜 1114\n",
      "韩国 310\n",
      "湘菜 75\n",
      "江苏菜 249\n",
      "满汉全席 44\n",
      "微波炉菜 85\n",
      "日本料理 11\n",
      "海派菜 19\n",
      "鲁菜 285\n",
      "川菜 352\n",
      "全部 1323\n",
      "云南菜 18\n",
      "淮阳菜 34\n",
      "东北菜 52\n",
      "闽菜 114\n",
      "法国名菜 53\n",
      "京菜 123\n",
      "粤菜 195\n",
      "其他西餐 34\n"
     ]
    }
   ],
   "source": [
    "from collections import Counter\n",
    "\n",
    "tps_cts = Counter(data_tps)\n",
    "\n",
    "for k, v in tps_cts.items():\n",
    "    print k, v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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fnHp86q1TFv/83tl3bEp0JjR0/QjjKlI/Wrmp2a/B3p8oEclk8vL9YYwpqgg4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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8b49070c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import cm\n",
    "\n",
    "_, ax = plt.subplots(figsize=(8, 8))\n",
    "ax.pie([v for k, v in tps_cts.items()], labels=[k for k, v in tps_cts.items()], colors=cm.Vega20.colors)\n",
    "ax.axis(\"equal\")\n",
    "for t in ax.texts:\n",
    "    t.set_font_properties(font_song)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "这里，类别为全部大概是没有菜系的意思吧（我猜的）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### 食材统计"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "食材统计是个比较麻烦的事情，先随便看看食材的数据长什么样子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "活雌鸡或阉鸡1只，约重1500～2000克，菜油（或化猪油）100克，豆瓣25克，老姜50克，大葱10克，白糖或冰糖25克，花椒、料酒、酱油、精盐、味精、八角等适量。\n",
      "燕窝（40克）、椰子（1个，750克）、味粉（15克）、鸡汤（250克）、精盐（少许）、小苏打粉（少许）\n",
      "活鳝鱼350克。虾仁50克、熟火腿20克、猪腰片50克、水发冬菇20克，水发虾米10克、熟笋片30克…虾子5克。猪肉汤750克、绍酒15克、葱15克、姜7.5克、盐5克、味精3克、白胡椒粉1.5克。\n",
      "光鸭（1只，1500克左右）、葱段（20克）、姜片（20克）、桂皮（20克）、茴香（13克）、红米（8克）、黄酒、冰糖（130克）、白酱、盐、麻油\n",
      "节瓜600克（约1斤），草菇50克（约1两半），虾仁100克（约2两半），蟹肉75克（约2两），蛋白1只，上汤400毫升，姜1片，葱1条。盐1茶匙，糖1/4茶匙，粟粉、酒各1茶匙，水1汤匙，胡椒粉少许。\n",
      "嫩母鸡（约1．25公斤左右）1只，胡萝卜100克，芹菜50克，葱头10O克，精盐10克，香叶半片，胡椒6粒，鸡清汤250毫升，生菜油500（罕耗100克），奶油15克，鸡油15克，红白菜200克，酸黄瓜100克，鲜西红柿100克，纸花2个，萝卜花2个，生菜叶10克。\n",
      "水发鱿鱼（325克）、京葱花（40克）、大蒜头片（10片）、黄酒（12.5克）、醋（少许）、盐（6克）、味精（少许）、酱瓜米（少许）、菱粉（45克）、清汤（150克）。\n",
      "鲜鱿鱼肉12两（约480克），西芹一条。西芹调味料：盐1/8茶匙，麻油少许。鱿鱼调味料：盐1/4茶匙，胡椒粉少许。椒麻汁料：花椒粒1茶匙，姜茸2茶匙，青葱茸2汤匙，糖2/3茶匙，醋，麻油各1茶匙，生抽，开水各2汤匙。\n",
      "原料：面条500克，菠菜或小白菜300克，青椒（甜）3个，榨菜25克。葱10克，蒜1头，酱油10克，香醋5克，精盐3克，味精2克，香油15克，高汤适量。\n",
      "主料扁豆150克，鸡油50克。调料料酒25克，味精5克，湿淀粉15克，鸡汤150克。\n"
     ]
    }
   ],
   "source": [
    "for i in range(0, 4000, 400):\n",
    "    print data[i][\"原料\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "为了搞定这些问题，我们可以想办法去掉里面的一些关键词，比如多少克，少许，越重以及标点符号："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "活雌鸡 阉鸡 菜油 豆瓣 老姜 大葱 白糖 冰糖 花椒 料酒 酱油 精盐 味精\n",
      "燕窝 椰子 味粉 鸡汤 精盐 小苏打粉\n",
      "活鳝鱼 虾仁 熟火腿 猪腰片 水发冬菇 水发虾米 熟笋片 虾子 猪肉汤 绍酒 葱 姜 盐 味精 白胡椒粉\n",
      "光鸭 葱段 姜片 桂皮 茴香 红米 黄酒 冰糖 白酱 盐 麻油\n",
      "节瓜 草菇 虾仁 蟹肉 蛋白 上汤 姜 葱 盐 糖 粟粉 酒 水 胡椒粉\n",
      "嫩母鸡 胡萝卜 芹菜 葱头 精盐 香叶 胡椒 鸡清汤 生菜油 奶油 鸡油 红白菜 酸黄瓜 鲜西红柿 纸花 萝卜花 生菜叶\n",
      "水发鱿鱼 京葱花 大蒜头片 黄酒 醋 盐 味精 酱瓜米 菱粉 清汤\n",
      "鲜鱿鱼肉 西芹 西芹 盐 麻油 鱿鱼 盐 胡椒粉 椒麻汁料 花椒粒 姜茸 青葱茸 糖 醋 麻油 生抽 开水\n",
      "面条 菠菜 小白菜 青椒 榨菜 葱 蒜 酱油 香醋 精盐 味精 香油 高汤\n",
      "扁豆 鸡油 料酒 味精 湿淀粉 鸡汤\n"
     ]
    }
   ],
   "source": [
    "def process_single_ingredient(line):\n",
    "    # 标点符号替换为空格\n",
    "    line = re.sub(\"[。，、/…~～：；:%]\", \" \", line) + \" \"\n",
    "    line = re.sub(\"（[^（]*）\", \" \", line)\n",
    "    # 阿拉伯数字替换为空格\n",
    "    line = re.sub(\"\\d+\\S* \", \" \", line)\n",
    "    # 汉语数字替换为空格\n",
    "    line = re.sub(\"[一二两三四五六七八九十几半]+\\S* \", \" \", line)\n",
    "    # 关键词替换为空格\n",
    "    for s in [\"少许\", \"适量\", \"或\", \"等\", \"重\", \"约\", \n",
    "              \"各\", \"原料\", \"调味料\", \"主料\", \"辅料\", \"调料\", \"用料\", \"和\", \"及\"]:\n",
    "        line = re.sub(s, \" \", line)\n",
    "    # 字母替换为空格\n",
    "    line = re.sub(\" \\w+ \", \" \", line)\n",
    "    line = re.sub(\" +\", \" \", line).strip()\n",
    "    return line\n",
    "\n",
    "for i in range(0, 4000, 400):\n",
    "    print process_single_ingredient(data[i][\"原料\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "这样结果就看起来不错的样子了，我们来做一下统计："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data_ings = map(lambda x: process_single_ingredient(x[\"原料\"]), data)\n",
    "data_ings_all = \" \".join(data_ings).split()\n",
    "\n",
    "ings_cts = Counter(data_ings_all)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "不出意外的话，排在前面的原料应该是各种调味品："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "酱油 1288\n",
      "花椒 252\n",
      "鸡蛋清 299\n",
      "鸡汤 399\n",
      "料酒 1048\n",
      "姜末 284\n",
      "水淀粉 254\n",
      "味精 2049\n",
      "姜 799\n",
      "麻油 351\n",
      "香油 460\n",
      "醋 434\n",
      "绍酒 808\n",
      "精盐 1520\n",
      "胡椒粉 801\n",
      "湿淀粉 619\n",
      "白糖 1140\n",
      "芝麻油 434\n",
      "葱 948\n",
      "盐 1452\n",
      "植物油 274\n",
      "油 277\n",
      "鸡蛋 506\n",
      "熟猪油 325\n",
      "淀粉 387\n",
      "葱段 237\n",
      "清汤 280\n",
      "猪油 225\n",
      "黄酒 243\n",
      "花生油 410\n",
      "糖 401\n",
      "面粉 261\n"
     ]
    }
   ],
   "source": [
    "for k, v in ings_cts.items():\n",
    "    if v > 200:\n",
    "        print k, v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### 食材预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "有了食材，我们可以按照那篇英文文章的想法，用一个食材预测的任务来得到食物的Embedding向量。\n",
    "\n",
    "那篇文章的想法是，我们用菜谱中的每个食材，来预测菜谱中除他之外的其它食材。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "我们现在的食材有："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5598"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ings_cts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "我们现在去除那些只出现了次数比较少的食材："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "for k in ings_cts.keys():\n",
    "    if ings_cts[k] <= 5:\n",
    "        ings_cts.pop(k)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "剩下的有："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "737"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ings_cts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "然后将他们编号："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "word_idx = {k: idx+1 for idx, k in enumerate(ings_cts)}\n",
    "idx_word = {idx+1: k for idx, k in enumerate(ings_cts)}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "接下来将数据id化："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data_ings_idx = map(lambda x: [word_idx.get(t, 0) for t in x.split()], data_ings) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### 模型构造"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "有了数据集，模型也就不难构造了："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "这里，我们使用`keras`来构造我们的`Embedding`模型："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import keras"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "因为使用的是`tensorflow`的后端，而且是GPU版本的，我需要设置一下GPU选项，免得我的小程序什么都没做就吃掉所有的GPU显存（坑爹的tensorflow能不能不要认为这些卡都是我一个人在用！）："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "import keras.backend as K\n",
    "\n",
    "if K.backend() == \"tensorflow\":\n",
    "    config = K.tf.ConfigProto()\n",
    "    config.gpu_options.allow_growth = True\n",
    "    session = K.tf.Session(config=config)\n",
    "    K.set_session(session)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "模型其实很简单，我们先构造一个`N×D`的`Embedding`矩阵，其中`N`是我的食材数目，`D`是我需要的食材向量的维度，那么`N`种食材就对应与这`N`个`D`维向量了。\n",
    "\n",
    "现在我们来构造这个模型："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Embedding, Dense, Flatten\n",
    "from keras.regularizers import l2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "模型是个`Embedding`层加一个`sigmoid`输出的全连接层`Dense`，输入维度为1，代表食材的种类，输出长度为`N`，代表这个食材与其它食材相关的概率。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "n_words = len(word_idx) + 1\n",
    "model = Sequential()\n",
    "model.add(Embedding(n_words, 50, input_length=1, activity_regularizer=l2(0.01)))\n",
    "model.add(Flatten())\n",
    "model.add(Dense(n_words, activation=\"sigmoid\", activity_regularizer=l2(0.01)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "model.compile(optimizer=\"adam\", loss=\"binary_crossentropy\", metrics=[\"acc\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "构造我们的训练集："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data_x = []\n",
    "data_y = []\n",
    "\n",
    "for ings_idxs in data_ings_idx:\n",
    "    if len(ings_idxs) == 1:\n",
    "        continue\n",
    "    for idx in set(ings_idxs):\n",
    "        y = np.zeros(n_words)\n",
    "        data_x.append(idx)\n",
    "        y[list(set(ings_idxs) - set([idx]))] = 1\n",
    "        data_y.append(y)\n",
    "        \n",
    "data_x = np.array(data_x)\n",
    "data_y = np.array(data_y)\n",
    "\n",
    "rd_idx = np.arange(len(data_x))\n",
    "np.random.shuffle(rd_idx)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "训练模型："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 1 completed\n",
      "epoch 2 completed\n",
      "epoch 3 completed\n",
      "epoch 4 completed\n",
      "epoch 5 completed\n"
     ]
    }
   ],
   "source": [
    "hist = model.fit(data_x[rd_idx], data_y[rd_idx], validation_split=0.1, verbose=0, epochs=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "训练完成，我们拿到这些Embedding的向量："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "emb = model.get_weights()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(738, 50)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "emb.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "算个距离度量，并看看一些跟食材最接近的都是什么："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "酱油\n",
      "鸡蛋\n",
      "高汤\n"
     ]
    }
   ],
   "source": [
    "from scipy.spatial import distance\n",
    "\n",
    "dist = distance.squareform(distance.pdist(emb, \"cosine\"))\n",
    "\n",
    "print idx_word[np.argsort(dist[word_idx[\"盐\"]])[1]]\n",
    "print idx_word[np.argsort(dist[word_idx[\"鸡汤\"]])[1]]\n",
    "print idx_word[np.argsort(dist[word_idx[\"西红柿\"]])[1]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "看起来还是蛮有意思的，然而并看不出什么靠谱的结论。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### 菜系预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "我们也可以用我们的数据来进行菜系预测，比如想象成一个序列预测问题，用一个输入序列来预测最终的菜系，序列处理可以使用一个`RNN`，比如`LSTM`，`GRU`等，这里我们随便用一个："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from keras.layers import LSTM, GRU\n",
    "from keras.preprocessing.sequence import pad_sequences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def process_rnn(line):\n",
    "    # 标点符号\n",
    "    line = re.sub(\"[。，、/…~～：；:%（）]\", \"\", line)\n",
    "    # 阿拉伯数字替换为空格\n",
    "    line = re.sub(\"[\\d\\w]\", \"\", line)\n",
    "    return line\n",
    "\n",
    "data_rnn = [process_rnn(i[\"原料\"]) for i in data]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "word_cts = Counter(\"\".join(data_rnn))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1105"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for k, v in word_cts.items():\n",
    "    if v == 1:\n",
    "        word_cts.pop(k)\n",
    "        \n",
    "len(word_cts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "word_idx = {k: idx+1 for idx, k in enumerate(word_cts)}\n",
    "idx_word = {idx+1: k for idx, k in enumerate(word_cts)}\n",
    "\n",
    "tps_idx = {k: idx for idx, k in enumerate(tps_cts)}\n",
    "idx_tps = {idx: k for idx, k in enumerate(tps_cts)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data_rnn_idx = map(lambda x: [word_idx.get(t, 0) for t in x], data_rnn)\n",
    "data_tps_idx = np.array(map(lambda x: tps_idx[x], data_tps))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data_rnn_idx = np.array(pad_sequences(data_rnn_idx))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "n_seq = len(data_rnn_idx[0])\n",
    "n_words = len(word_idx) + 1\n",
    "n_tps = len(tps_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "rnn_model = Sequential()\n",
    "rnn_model.add(Embedding(n_words, 64, input_length=n_seq))\n",
    "rnn_model.add(GRU(64))\n",
    "rnn_model.add(Dense(128, activation=\"relu\", name=\"feat\"))\n",
    "rnn_model.add(Dense(n_tps, activation=\"softmax\"))\n",
    "\n",
    "rnn_model.compile(optimizer=\"adam\", loss=\"sparse_categorical_crossentropy\", metrics=[\"acc\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "hist = rnn_model.fit(data_rnn_idx, data_tps_idx,\n",
    "                     epochs=50, verbose=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "准确率为："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.90364867817347605"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist.history[\"acc\"][-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "我们现在把最后一层的特征拿出来："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from keras.models import Model\n",
    "feat_model = Model(inputs=rnn_model.input, outputs=rnn_model.get_layer(\"feat\").output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data_feat = feat_model.predict(data_rnn_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4577, 128)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_feat.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "做一个TSNE降到2维："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from sklearn.manifold import TSNE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data_feat_vis = TSNE(n_components=2, init='pca').fit_transform(data_feat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4577, 2)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_feat_vis.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "可视化一下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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y8A0NgxYRERERUSMQ5OdsdbCqraKiAoGBgXBwcICzszN69OiBlStXIjY2FhcuXMD8+fO1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BAAAg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\nCFoAAAAAELL/D9/RYLc2C1oYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f896aa8a590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(figsize=(15, 12))\n",
    "for tp, idx in tps_idx.items():\n",
    "    ax.scatter(data_feat_vis[data_tps_idx==idx, 0], data_feat_vis[data_tps_idx==idx, 1], \n",
    "               c=cm.Vega20.colors[idx], label=tp)\n",
    "\n",
    "ax.set_xlim(-20, 40)\n",
    "ax.set_ylim(-20, 20)\n",
    "ax.set_xticks([])\n",
    "ax.set_yticks([])\n",
    "\n",
    "ax.legend(loc=0)\n",
    "ltext = ax.get_legend().get_texts()\n",
    "for t in ltext:\n",
    "    t.set_font_properties(font_song)\n",
    "    t.set_fontsize(\"xx-large\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "- 韩国菜明显风格跟天朝有差异\n",
    "- 浙江菜的隔壁是沪菜和江苏菜，江苏菜的隔壁是鲁菜\n",
    "- 微波炉菜（不知道什么鬼）混入了全部菜系之中\n",
    "- 闽菜和粤菜相邻\n",
    "- 粤菜的点分布的还挺开的（大概广东人什么都吃？）\n",
    "- 湘菜跟川菜也挺近的\n",
    "\n",
    "剩下的请恕我老眼昏花看不清楚，从地理上看，还是有点意思的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "> 人生呐，就该一本正经地胡说八道。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
